1. Field
The disclosed embodiments relate to Internet traffic. More specifically, the disclosed embodiments relate to methods of evaluating the trustworthiness of Internet traffic.
2. Related Art
The Internet increasingly facilitates more and more transactions between parties. In such transactions, it is important for parties to the transaction to have a certain level of trust or confidence that the other party is not acting fraudulently. This may be difficult in online environments because transactions are completed remotely and anonymously. Methods have been developed to increase trust in transactions, such as by requiring user names and passwords to complete a transaction, or soliciting feedback to verify the presence of a real person instead of a bot (an automated program on a computer running automatically).
However, in some instances, transactions are of a nature that no such traditional mechanisms are not possible. For example, when advertising or other content is presented over the Internet, user names and passwords are traditionally not required to access the content. In many instances, it would be unproductive and undesirable to require such input from the user to access such content. In some instances, trust in these transactions often depends at least in part on knowing a location of a user requesting the transaction. Typically, locations are determined by mapping databases or files that connect an IP address to the last known longitude and latitude of the IP address. However, such files may become quickly outdated. Further, these techniques may be circumvented by several technologies such as virtual private networks (“VPN”) or Tor that enable a user to masquerade his or her true location.
Returning to the example of online advertising as an Internet transaction, online advertising or other similar content is presented on various websites. The ability of various websites to attract advertising revenue is based largely on Internet traffic, where traffic is defined as Internet users accessing a web site or requesting content. Website publishers strive to develop the most relevant and interesting content to attract and drive traffic to their sites. The more traffic that a website has, the more advertising revenue the website can generate based on more page requests or click-throughs for a given advertisement. Websites that drive a high amount of Internet traffic may charge more for advertising space on the website. Additionally, advertising algorithms that determine ad placement across several websites may target placement on sites with a high amount of web traffic.
The above-described online adverting environment thus creates a premium on web traffic. This has led to an unfortunate rise in fraudulent web traffic. Fraudulent web traffic may be generated from a variety of sources including through redirects, hidden or embedded web pages, and botnets including computers dedicated to fraudulent activities and/or computers infected by malware. Fraudsters may use this fraudulent traffic to drive more advertising on their sites (or on websites of those buying the traffic from the fraudsters) and to collect revenue for advertisement requests or click-throughs.
For example, much of online advertisement placement is determined automatically based on Internet traffic analytics. In other words, advertisement placement is increasingly being determined via software algorithms instead of face-to-face negotiations between an advertiser and a website operator. Thus, fraudulent traffic may be utilized by some websites to gain more advertisement placements, even though the Internet traffic on their website is non-human in nature.
Many advertisers look to online advertising as a method of advertising that may provide accurate feedback concerning the effectiveness of an advertising campaign as compared to conventional advertising via print, television, radio, or other such mediums. However, this has not turned out to be the case. While advertisers may obtain feedback for online advertisements such as a number of requests for a given advertisement by different websites, the information has not proven to be more reliable than feedback from other mediums such as a billboard advertisement.
There are many reasons for the lack of reliable analytics for online advertising. For example, while the number of requests for an advertisement may be tracked, it is impossible to tell whether a real end user had an opportunity to view the advertisement requested. This may be the case for a number of different reasons.
One such reason is, again, fraudulent internet traffic. It is difficult for companies and the advertisers that they employ to determine if the ad is truly being viewed by a user, or whether a human user is even responsible for the display of the ad. As is understood in the art, numerous methods exist for an automated computer to request an online advertisement without human intervention. These methods may include botnets, viruses, malware, or hidden frames on web pages that may request the ad for display or may provide the appearance that the ad is displayed, even though it is not. This is a serious concern for a company or advertiser as each ad request may require a payment to be made or may count toward a fixed number of ad display instances which were purchased. By some estimates, up to 50% of the ad traffic may be generated by such non-human activity.
Other reasons that a requested advertisement may not be viewed by a real end user is simply that the user is not scrolling to a portion of the webpage where the advertisement is placed. In other words, the advertisement may not be on a viewable portion of the display window. Another reason is simply that no user is currently viewing a screen on which an advertisement is displayed.
Thus, advertisers still need more reliable information concerning whether advertisements placed online are requested by a human and effectively being conveyed to and viewed by an end user and driving that user's behavior. In other applications, content providers, online merchants, and other parties connected to the Internet need relevant feedback of whether a third-party viewing content or attempting to make a transaction is trustworthy.